In our years building decision intelligence models for domains like banking, telecom, and more, the project that I am most proud of is the work that we did for Liberia in collaboration with The Carter Center. The basic idea: countries are complex systems. "

We are shifting our thinking style to accommodate a much more complex and interdependent world than we have faced in the past. Consider: In 2014, Google purchased Deep Mind, formerly a UK-based startup with a focus on "Neural Turing Machines".       Deep Mind's unique approach: to use video game play as a learning environment,…

According to Ben Ramalingam’s Aid on the Edge of Chaos, international development is just such an invasive species. Why Dertu doesn’t have a vaccination clinic, why Kenyan schoolkids can’t read, it’s a combination of culture, politics, history, laws, infrastructure, individuals—all of a society’s component parts, their harmony and their discord, working as one organism. Introducing something foreign into that system—millions in donor cash, dozens of trained personnel and equipment, U.N. Land Rovers—causes it to adapt in ways you can’t predict.

...for a widespread class of situations, predictive analytics alone aren’t enough. Consider the decision model below, which I introduced in my last post. The blue graphs on the right-hand side are based on predictive analytics, but they are only building blocks in the full model. They are not enough on their own."

"The model ... mixes ingredients from machine learning, big data, intelligence augmentation, predictive analytics, dashboards, complex systems analysis, causal modeling, agency theory, statistical analysis, and more in a way that answers the most practical of all questions: If I make this decision today, how will it impact my future business objectives?"

"...What’s less well-known about the marshmallow study is that delayed gratification can be taught. Says this article, “‘Impulsivity,’ [the authors] concluded, ‘is not a purely maladaptive trait, but one whose consequences hinge on the structure of the decision-making environment.'"

The software engineering revolution is happening again. I was a coder before software engineering, and it wasn't pretty.  When we needed to build a new program, we'd get together with the end customer, and ask a lot of questions, then go back to the office to write code.  It didn't go very well.  It was…

Delivery of big data analytics to all roles within a company — no matter the size — will make "Decision Process Reengineering" to the next decade what "Business Process Reengineering" has been to the previous two decades. It’s as simple as that.

Throughout the history of machine learning, there have been tools that have tried to make it easier to build a learner, with a focus on the "practitioner" rather than the research scientist or professional software developer.  These systems have come and gone, but none seem to have really taken off. This time, it's is different.…

"...the stakes are rising as the methods and mind-set of data science spread across the economy and society. Big companies and start-ups are beginning to use the technology in decisions like medical diagnosis, crime prevention and loan approvals. The application of data science to such fields raises questions of when close human supervision of an algorithm’s results is needed."

OK, I'll admit it. AI scares me.  But not for the usual reasons: I'm not too concerned about robots taking over the earth or even the Singularity, as are many of my friends.  What does frighten me is the distraction that AI represents from the problems that matter.  The ones that need our judgment, our ethics, our humanity,…

Instead of traditional analytics, where the analytics is done on a given data set, decision engineering involves working with key decision-makers, such as CMO, CTOs, CXOs to understand what are their pain-points and then figure out what are the various data levers we can apply to help them take the decisions. It is not a canned approach. So for the same problem you would need a combination of data such as market research, big data or may be large data sitting with a company's customer base. Decision engineering brings all the data in the company together to enable decision-making.

And how you can avoid them.

I am not a data scientist. I repeat, I am not a data scientist. Last week I spoke on a panel with the author of this blog and several other decision intelligence executives. Our topic, “Who is Your Chief Decision Officer”, was a hit. The discussion centered on the fact that the data and technology…

In anticipation of Mark Zangari's upcoming talk on Agency Theory at MLConf Seattle, a question appeared on Quora yesterday asking  "What is the World Modeler platform and how does it compare to similar platforms?" 

"Since the datasets available in these fields are small, data scientists cannot apply pre-packaged Deep Learning algorithms, but have to artfully determine the features to train and engineer their networks with convolution/dense layers to learn these rather complex features. The data scientists that perform these tasks have to be machine learning engineers who walked in the shoes of a radiologists, internist or a chemical engineer."

We've been lost in data for half a century. Time to move on, friends. Robert McNamara, secretary of defense from 1961 through 1968, came to the post from Ford Motor company, where he was ultimately appointed president.  His success in both positions came from bringing the discipline of statistical control from the Air Force into Ford"

As far as we know, AIDR is the only Big Data solution out there that combines crowdsourcing with real-time machine learning for disaster response. Why do we use crowdsourcing to train the AI engine? Because speed is of the essence in disasters. You need a crowd of Digital Humanitarians to quickly tag as many tweets/messages as possible so that AIDR can learn as fast as possible. Incidentally, once you’ve created an algorithm that accurately detects tweets relaying urgent needs after a Typhoon in the Philippines, you can use that same algorithm again when the next Typhoon hits (no crowd needed).